Reduced support vector machine detector for Chaos-based CDMA systems

J. Kao, S. Berber, V. Kecman
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引用次数: 1

Abstract

In this paper, we present the algorithm and the results of a modified support vector machine (SVM) detector on a Chaos-based code division multiple access (CDMA) system so that it has less computational complexity than the conventional correlator receiver. This is achieved through the recursive feature elimination (RFE) algorithm, which is commonly used for feature extraction in bioinformatics applications. The system was simulated under both AWGN and Rayleigh fading channels. Simulation results showed that the modified scheme has less complexity than the conventional correlator and provides a much better BER performance. The maximum performance loss is only 2 dB away from a standard SVM detector under AWGN and no significant difference was observed under the Rayleigh fading channel.
基于混沌的CDMA系统的简化支持向量机检测器
本文提出了一种改进的支持向量机(SVM)检测器在基于混沌的码分多址(CDMA)系统上的算法和结果,使其比传统的相关器接收器具有更低的计算复杂度。这是通过递归特征消除(RFE)算法实现的,该算法通常用于生物信息学应用中的特征提取。在AWGN和瑞利衰落信道下对系统进行了仿真。仿真结果表明,改进后的方案比传统的相关器具有更低的复杂度和更好的误码率性能。在AWGN下,最大性能损失与标准SVM检测器相差仅2 dB,在瑞利衰落信道下无显著差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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